High Performance Python: Practical Performant Programming for Humans - Softcover

Über die Autorinnen und Autoren

Micha Gorelick has worked as a machine learning researcher and engineer for The Markup and OCCRP. She was the co-founder of an applied machine learning company, Fast Forward Labs and authored the book ÂœHigh Performance Python. She has worked as the lead researcher on a variety of cutting-edge research projects on topics ranging from neural networks for text summarization, probabilistic programming for understanding housing prices and various machine learning approaches for journalism.

Ian Ozsvald is a chief data Scientist and coach. He co-organizes the annual PyDataLondon conference with 700+ attendees and the associated 15,000+ member monthly meetup. He runs the established Mor Consulting data science consultancy in London and gives conference talks internationally, often as keynote speaker. He has 26 years of experience as a senior data science leader, trainer, and team coach. Noting the absence of advice for senior leaders he established the RebelAI data science leadership community in 2023, having helped many clients at a strategic level since 2015. For fun, he's walked by his high-energy Springer Spaniel, surfs the Cornish coast, and drinks fine coffee. Past talks and articles can be found at https: //ianozsvald.com.

Von der hinteren Coverseite

Your Python code may run correctly, but what if you need it to run faster? This practical book shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By explaining the fundamental theory behind design choices, this expanded edition of High Performance Python helps experienced Python programmers gain a deeper understanding of Python's implementation.

How do you take advantage of multicore architectures or compilation? Or build a system that scales up beyond RAM limits or with a GPU? Authors Micha Gorelick and Ian Ozsvald reveal concrete solutions to many issues and include war stories from companies that use high-performance Python for GenAI data extraction, productionized machine learning, and more.

• Get a better grasp of NumPy, Cython, and profilers
• Learn how Python abstracts the underlying computer architecture
• Use profiling to find bottlenecks in CPU time and memory usage
• Write efficient programs by choosing appropriate data structures
• Speed up matrix and vector computations
• Process DataFrames quickly with Pandas, Dask, and Polars
• Speed up your neural networks and GPU computations
• Use tools to compile Python down to machine code
• Manage multiple I/O and computational operations concurrently
• Convert multiprocessing code to run on local or remote clusters